Build walkthrough · Pinnacle Tech Projects

From invisible to cited.
I built an AI-visibility platform in a day.

AEO Command tells a local business exactly how often ChatGPT, Perplexity, Google AI and Claude recommend them — and the precise steps to get cited more. Watch the whole thing get built with Claude, Supabase, DataForSEO and n8n.

61%AI visibility
10Prompts
4Engines
1607Bot visits 7d
10Actions
The video

Watch the full build

Idea to working multi-tenant dashboard — schema, automations, AI engines and all.

Watch — How I built AEO Command
Why it matters

People stopped Googling. They started asking.

When someone asks an AI "who's the best landscaper in Toronto?", a handful of businesses get named — and the rest are invisible. AEO Command measures exactly where a business stands across every major engine, then turns the gaps into a plan.

Measure

Run a client's prompts through ChatGPT, Perplexity, Google AI and Claude and track how often they're named.

Diagnose

See the exact sources the AI cites — the directories, review sites and listicles where competitors show up and you don't.

Act

Get a prioritized, do-this-next action plan — "create a HomeStars profile", "claim your Google Business Profile".

Under the hood

One clean pipeline

Claude orchestrates the whole stack through MCP — then the stack runs itself.

Claude
Agent orchestrator. Designs the schema, writes the SQL, builds the automations and the app — via MCP.
Agent
Supabase MCP
Postgres for AEO: tenants, prompts, runs, citations, bot visits, opportunities + views.
MCP / Data
DataForSEO MCP
The signal source: live answers from 4 AI engines, SERP, and the citations behind each.
MCP / Signal
n8n
Automation: onboarding, the multi-engine daily runner, and DataForSEO enrichment — writing back to Supabase.
Workflows
React
The AEO Command dashboard — reads Supabase and renders visibility, citations, the action plan and crawler traffic.
UI

Runtime data flow

1

A schedule fires in n8n (or you hit refresh).

2

It pulls the client's prompts from Supabase.

3

Each prompt hits ChatGPT, Perplexity, Gemini & Claude via DataForSEO.

4

n8n captures the mention and the cited sources.

5

Results are written back to Supabase.

6

The React dashboard renders every tab.

Built entirely by an agent

No boilerplate, no scaffolding by hand. Claude ran the database design, wrote and validated the n8n workflows, generated the React dashboard, seeded a demo tenant, and even built a self-contained demo workflow for this video — all by calling the tools directly through MCP.

Claude · agent Supabase · Postgres DataForSEO · AI/SEO data n8n · automation React · Vite
The dashboard

Six views, one story

From the headline visibility score down to the exact next move.

Overview

Visibility trend, per-engine scores, crawler traffic and top cited sources at a glance.

Prompts

Where you're winning vs. where you're invisible — the keyword-level work queue.

Citations

The roadmap: which domains the AI looks at before it answers — and whether you're there.

Action Plan

A prioritized, do-this-next checklist with a status pipeline from identified to cited.

Bot Traffic

AI crawler visits over time — the leading indicator that the work is landing.

Architecture

The whole system on one screen — Claude to Supabase to DataForSEO to n8n to React.

4AI engines tracked
50+Prompts per client
5n8n workflows
1URL to onboard a client
What's next

A white-label platform for local agencies

Measure AI visibility, hand clients an exact action plan, and prove the lift over time — under your own brand.

▸ Watch the build Get in touch